probability_exact_time_varying

Computes the probability of being seropositive when
Forces-of-Infection (FoIs) vary by time

Estimating the force of infection from time varying, age varying, or constant
serocatalytic models from population based seroprevalence studies using a Bayesian framework,
including data simulation functions enabling the generation of serological surveys based on this
models. This tool also provides a flexible prior specification syntax for the force of infection
and the seroreversion rate, as well as methods to assess model convergence and comparison
criteria along with useful visualisation functions.

Zulma M. Cucunubá

serofoi

Bayesian Estimation of the Force of Infection from Serological
Data

Nicolás T. Domínguez

Ben Lambert

Pierre Nouvellet

Geraldine Gómez

Jaime A. Pavlich-Mariscal

Hugo Gruson

David Santiago Quevedo

Miguel Gámez

Sumali Bajaj

Everlyn Kamau

Richard Creswell

International Development Research Center (IDRC) 

Pontificia Universidad Javeriana 

probability_exact_time_varying function

<dl><dt>years</dt>
<dd>Integer indicating the years covering the birth ages of the
sample</dd>
<dt>fois</dt>
<dd>Numeric atomic vector corresponding to the age-varying
FoI to simulate from</dd>
<dt>seroreversion_rate</dt>
<dd>Non-negative seroreversion rate. Default is 0.</dd></dl>

Arguments

Computes the probability of being seropositive when
Forces-of-Infection (FoIs) vary by time — probability_exact_time_varying

<dl>

<dt>years</dt>
<dd>Integer indicating the years covering the birth ages of the
sample</dd>


<dt>fois</dt>
<dd>Numeric atomic vector corresponding to the age-varying
FoI to simulate from</dd>


<dt>seroreversion_rate</dt>
<dd>Non-negative seroreversion rate. Default is 0.</dd>

</dl>

Computes the probability of being seropositive when
Forces-of-Infection (FoIs) vary by time

probability_exact_time_varying: Computes the probability of being seropositive when Forces-of-Infection (FoIs) vary by time

Description

Usage

Value

Arguments